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Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach

Author

Listed:
  • Hu-Chen Liu

    (Shanghai University
    Tongji University)

  • Yi-Zeng Chen

    (Shanghai University)

  • Jian-Xin You

    (Shanghai University
    Tongji University)

  • Hui Li

    (Tongji University
    Tongji University)

Abstract

Failure mode and effects analysis (FMEA) is a widely used engineering technique for identifying and eliminating known and potential failures from systems, designs, products, processes or services. However, the conventional risk priority number method has been extensively criticized in the literature for a lot of reasons such as ignoring relative importance of risk factors, questionable multiplication procedure, and imprecisely evaluation. In this article, a new FMEA model based on fuzzy digraph and matrix approach is developed to solve the problems and improve the effectiveness of the traditional FMEA. All the information about risk factors like occurrence (O), severity (S) and detection (D) and their relative weights are expressed in linguistic terms, represented by fuzzy numbers. By considering the risk factors and their relative importance, a risk factors fuzzy digraph is developed for the optimum representation of interrelations. Then, corresponding fuzzy risk matrixes are formed for all the identified failure modes in FMEA and risk priority indexes are computed for determining the risk priorities of the failure modes. Finally, a case study of steam valve system is included to illustrate the proposed fuzzy FMEA and the advantages are highlighted by comparing with the listed methods.

Suggested Citation

  • Hu-Chen Liu & Yi-Zeng Chen & Jian-Xin You & Hui Li, 2016. "Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach," Journal of Intelligent Manufacturing, Springer, vol. 27(4), pages 805-816, August.
    • Handle: RePEc:spr:joinma:v:27:y:2016:i:4:d:10.1007_s10845-014-0915-6
    DOI: 10.1007/s10845-014-0915-6
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    Citations

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    Cited by:

    1. Zhen Wang & Rongxi Wang & Wei Deng & Yong Zhao, 2022. "An Integrated Approach-Based FMECA for Risk Assessment: Application to Offshore Wind Turbine Pitch System," Energies, MDPI, vol. 15(5), pages 1-25, March.
    2. Jianghong Zhu & Bin Shuai & Rui Wang & Kwai-Sang Chin, 2019. "Risk Assessment for Failure Mode and Effects Analysis Using the Bonferroni Mean and TODIM Method," Mathematics, MDPI, vol. 7(6), pages 1-17, June.
    3. Hasin Md. Muhtasim Taqi & Humaira Nafisa Ahmed & Sumit Paul & Maryam Garshasbi & Syed Mithun Ali & Golam Kabir & Sanjoy Kumar Paul, 2020. "Strategies to Manage the Impacts of the COVID-19 Pandemic in the Supply Chain: Implications for Improving Economic and Social Sustainability," Sustainability, MDPI, vol. 12(22), pages 1-25, November.
    4. Kübra Yazıcı & Seda Hatice Gökler & Semra Boran, 2021. "An integrated SMED-fuzzy FMEA model for reducing setup time," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1547-1561, August.
    5. Pushparenu Bhattacharjee & Syed Abou Iltaf Hussain & V. Dey & U. K. Mandal, 2023. "Failure mode and effects analysis for submersible pump component using proportionate risk assessment model: a case study in the power plant of Agartala," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1778-1798, October.
    6. María Carmen Carnero, 2020. "Waste Segregation FMEA Model Integrating Intuitionistic Fuzzy Set and the PAPRIKA Method," Mathematics, MDPI, vol. 8(8), pages 1-29, August.
    7. Hamzeh Soltanali & Abbas Rohani & Mohammad Hossein Abbaspour-Fard & Aditya Parida & José Torres Farinha, 2020. "Development of a risk-based maintenance decision making approach for automotive production line," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(1), pages 236-251, February.
    8. Hisham Alidrisi, 2021. "An Innovative Job Evaluation Approach Using the VIKOR Algorithm," JRFM, MDPI, vol. 14(6), pages 1-19, June.
    9. Zhaoguang Xu & Yanzhong Dang & Peter Munro & Yuhang Wang, 2020. "A data-driven approach for constructing the component-failure mode matrix for FMEA," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 249-265, January.
    10. Habib Zare Ahmadabadi & Fatemeh Zamzam & Farahnaz Rahmani Meybodi & Dalia Streimikiene & Abbas Mardani, 2018. "Developent of a New Sesame Product using QFD and DOE methods: A Case Study of Sesame Product in Yazd," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 14(1), pages 27-44.
    11. Hongzhan Ma & Xuening Chu & Deyi Xue & Dongping Chen, 2019. "Identification of to-be-improved components for redesign of complex products and systems based on fuzzy QFD and FMEA," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 623-639, February.
    12. Linlin Liu & Dongming Fan & Zili Wang & Dezhen Yang & Jingjing Cui & Xinrui Ma & Yi Ren, 2019. "Enhanced GO methodology to support failure mode, effects and criticality analysis," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1451-1468, March.
    13. Heng Zhang & Yaya Chen & Jingyu Cong & Junxiao Liu & Zhifu Zhang & Xirui Zhang, 2023. "Reliability Study of an Intelligent Profiling Progressive Automatic Glue Cutter Based on the Improved FMECA Method," Agriculture, MDPI, vol. 13(8), pages 1-17, July.
    14. Changfeng Yuan & Hui Cui & Bin Tao & Siming Ma, 2018. "Cause factors in emergency process of fire accident for oil–gas storage and transportation based on fault tree analysis and modified Bayesian network model," Energy & Environment, , vol. 29(5), pages 802-821, August.
    15. Huang, Jia & Li, Zhaojun(Steven) & Liu, Hu-Chen, 2017. "New approach for failure mode and effect analysis using linguistic distribution assessments and TODIM method," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 302-309.

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